基于故障预测的汽车备件动态库存优化方法和系统
By using a fault prediction-based approach, leveraging vehicle sensor data and historical mileage data, and combining this with a dynamic inventory control model, the reorder point and order quantity for automotive spare parts are optimized. This addresses the issue of existing technologies failing to consider internal factors and non-stationary demand, thereby reducing inventory management costs and improving response speed.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HEFEI UNIV OF TECH
- Filing Date
- 2023-08-08
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies fail to effectively consider the intrinsic factors affecting product demand and the non-stability of spare parts demand, leading to improper inventory management, which may result in customer losses or increased inventory costs.
By using a fault prediction-based approach, leveraging vehicle sensor data and historical mileage data, and combining this with a dynamic inventory control model, we can optimize the reorder point and order quantity for automotive spare parts, taking into account the inherent fault patterns and demand fluctuations of the spare parts.
It enables accurate forecasting of automotive spare parts demand, reduces inventory management costs, and improves responsiveness to customer needs and inventory optimization efficiency.
Smart Images
Figure CN117114572B_ABST